Content, progress and pedagogy of the module

Learning objectives

Knowledge

• Mass- and energy balances
• Preservation of momentum
• Definition of control volumes, Reynolds theorem
• Empirical relations for heat transfer friction
• Properties for liquids and gasses
• Fundamental laws of thermodynamics
• Models with lumped parameters¨
• Models with distributed parameters
• Model structures for system identification: AR, MA, ARMA, ARMAX, Box-Jenkins
• System identification methods: Moment method , Least squares method, Prediction error method, Maximum likelihood method, Recursive and adaptive parameter estimation
• Lagrange and Hamiltonian mechanics
• Coordinate systems and coordinate transformation for mechanical systems.
• Rotation parameters, rotation matrices, quaternions
• Kinematics
• Satellite and Robot dynamics
• Model representations (differential equations, state space, transfer function, differential-algebraic equations, descriptor form)
• Model reduction
• Linearization
• Model properties (controllability, observability, stability)

Skills

• Should be able to formulate models of a basic energy conversion systems and mechanical systems.
• Should be able to apply system identification methods
• Should be able to adapt the model to a suitable representation.

Competences

• Capable of modeling a system with sufficient information level, suitable for solving a given control problem

Type of instruction

As described in § 17.

Exam

Exams